{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "e485b65d",
   "metadata": {},
   "outputs": [],
   "source": [
    "import tensorflow as tf\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "107076d2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Education</th>\n",
       "      <th>Income</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>26.658839</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>10.401338</td>\n",
       "      <td>27.306435</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>10.842809</td>\n",
       "      <td>22.132410</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>11.244147</td>\n",
       "      <td>21.169841</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>11.645485</td>\n",
       "      <td>15.192634</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>12.086957</td>\n",
       "      <td>26.398951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>12.488294</td>\n",
       "      <td>17.435307</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>12.889632</td>\n",
       "      <td>25.507885</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>13.290970</td>\n",
       "      <td>36.884595</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>13.732441</td>\n",
       "      <td>39.666109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>14.133779</td>\n",
       "      <td>34.396281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>14.535117</td>\n",
       "      <td>41.497994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>14.976589</td>\n",
       "      <td>44.981575</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>15.377926</td>\n",
       "      <td>47.039595</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15</td>\n",
       "      <td>15.779264</td>\n",
       "      <td>48.252578</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>16</td>\n",
       "      <td>16.220736</td>\n",
       "      <td>57.034251</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>17</td>\n",
       "      <td>16.622074</td>\n",
       "      <td>51.490919</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>18</td>\n",
       "      <td>17.023411</td>\n",
       "      <td>61.336621</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19</td>\n",
       "      <td>17.464883</td>\n",
       "      <td>57.581988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20</td>\n",
       "      <td>17.866221</td>\n",
       "      <td>68.553714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21</td>\n",
       "      <td>18.267559</td>\n",
       "      <td>64.310925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>22</td>\n",
       "      <td>18.709030</td>\n",
       "      <td>68.959009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>23</td>\n",
       "      <td>19.110368</td>\n",
       "      <td>74.614639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>24</td>\n",
       "      <td>19.511706</td>\n",
       "      <td>71.867195</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>25</td>\n",
       "      <td>19.913043</td>\n",
       "      <td>76.098135</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>26</td>\n",
       "      <td>20.354515</td>\n",
       "      <td>75.775218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>27</td>\n",
       "      <td>20.755853</td>\n",
       "      <td>72.486055</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>28</td>\n",
       "      <td>21.157191</td>\n",
       "      <td>77.355021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>29</td>\n",
       "      <td>21.598662</td>\n",
       "      <td>72.118790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>30</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>80.260571</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Unnamed: 0  Education     Income\n",
       "0            1  10.000000  26.658839\n",
       "1            2  10.401338  27.306435\n",
       "2            3  10.842809  22.132410\n",
       "3            4  11.244147  21.169841\n",
       "4            5  11.645485  15.192634\n",
       "5            6  12.086957  26.398951\n",
       "6            7  12.488294  17.435307\n",
       "7            8  12.889632  25.507885\n",
       "8            9  13.290970  36.884595\n",
       "9           10  13.732441  39.666109\n",
       "10          11  14.133779  34.396281\n",
       "11          12  14.535117  41.497994\n",
       "12          13  14.976589  44.981575\n",
       "13          14  15.377926  47.039595\n",
       "14          15  15.779264  48.252578\n",
       "15          16  16.220736  57.034251\n",
       "16          17  16.622074  51.490919\n",
       "17          18  17.023411  61.336621\n",
       "18          19  17.464883  57.581988\n",
       "19          20  17.866221  68.553714\n",
       "20          21  18.267559  64.310925\n",
       "21          22  18.709030  68.959009\n",
       "22          23  19.110368  74.614639\n",
       "23          24  19.511706  71.867195\n",
       "24          25  19.913043  76.098135\n",
       "25          26  20.354515  75.775218\n",
       "26          27  20.755853  72.486055\n",
       "27          28  21.157191  77.355021\n",
       "28          29  21.598662  72.118790\n",
       "29          30  22.000000  80.260571"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data=pd.read_csv(\"data/Income1.csv\")\n",
    "pd.read_csv(\"data/Income1.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "be5dc895",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7f4efa5b85b0>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(data.Education,data.Income)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "1ee2c70b",
   "metadata": {},
   "outputs": [],
   "source": [
    "model=tf.keras.models.Sequential()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "6b21aa38",
   "metadata": {},
   "outputs": [],
   "source": [
    "model.add(tf.keras.layers.Dense(1,input_shape=(1,),activation='relu'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "8b45946b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"sequential\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "dense (Dense)                (None, 1)                 2         \n",
      "=================================================================\n",
      "Total params: 2\n",
      "Trainable params: 2\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "6fea2765",
   "metadata": {},
   "outputs": [],
   "source": [
    "model.compile(\n",
    "loss='mse',\n",
    "    optimizer='adam'\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "54939bb7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/5000\n",
      "1/1 [==============================] - 0s 457ms/step - loss: 1321.6398\n",
      "Epoch 2/5000\n",
      "1/1 [==============================] - 0s 7ms/step - loss: 1320.4315\n",
      "Epoch 3/5000\n",
      "1/1 [==============================] - 0s 5ms/step - loss: 1319.2240\n",
      "Epoch 4/5000\n",
      "1/1 [==============================] - 0s 7ms/step - loss: 1318.0170\n",
      "Epoch 5/5000\n",
      "1/1 [==============================] - 0s 6ms/step - loss: 1316.8105\n",
      "Epoch 6/5000\n",
      "1/1 [==============================] - 0s 7ms/step - loss: 1315.6049\n",
      "Epoch 7/5000\n",
      "1/1 [==============================] - 0s 7ms/step - loss: 1314.3998\n",
      "Epoch 8/5000\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 1313.1954\n",
      "Epoch 9/5000\n",
      "1/1 [==============================] - 0s 9ms/step - loss: 1311.9917\n",
      "Epoch 10/5000\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 1310.7886\n",
      "Epoch 11/5000\n",
      "1/1 [==============================] - 0s 10ms/step - loss: 1309.5863\n",
      "Epoch 12/5000\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 1308.3849\n",
      "Epoch 13/5000\n",
      "1/1 [==============================] - 0s 10ms/step - loss: 1307.1837\n",
      "Epoch 14/5000\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 1305.9835\n",
      "Epoch 15/5000\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 1304.7843\n",
      "Epoch 16/5000\n",
      "1/1 [==============================] - 0s 10ms/step - loss: 1303.5854\n",
      "Epoch 17/5000\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 1302.3875\n",
      "Epoch 18/5000\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 1301.1902\n",
      "Epoch 19/5000\n",
      "1/1 [==============================] - 0s 12ms/step - loss: 1299.9939\n",
      "Epoch 20/5000\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 1298.7983\n",
      "Epoch 21/5000\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 1297.6034\n",
      "Epoch 22/5000\n",
      "1/1 [==============================] - 0s 12ms/step - loss: 1296.4094\n",
      "Epoch 23/5000\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 1295.2161\n",
      "Epoch 24/5000\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 1294.0234\n",
      "Epoch 25/5000\n",
      "1/1 [==============================] - 0s 12ms/step - loss: 1292.8318\n",
      "Epoch 26/5000\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 1291.6410\n",
      "Epoch 27/5000\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 1290.4508\n",
      "Epoch 28/5000\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 1289.2617\n",
      "Epoch 29/5000\n",
      "1/1 [==============================] - 0s 16ms/step - loss: 1288.0735\n",
      "Epoch 30/5000\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 1286.8859\n",
      "Epoch 31/5000\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 1285.6991\n",
      "Epoch 32/5000\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 1284.5133\n",
      "Epoch 33/5000\n",
      "1/1 [==============================] - 0s 14ms/step - loss: 1283.3281\n",
      "Epoch 34/5000\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 1282.1440\n",
      "Epoch 35/5000\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 1280.9607\n",
      "Epoch 36/5000\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 1279.7781\n",
      "Epoch 37/5000\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 1278.5963\n",
      "Epoch 38/5000\n",
      "1/1 [==============================] - 0s 14ms/step - loss: 1277.4156\n",
      "Epoch 39/5000\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 1276.2357\n",
      "Epoch 40/5000\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 1275.0568\n",
      "Epoch 41/5000\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 1273.8785\n",
      "Epoch 42/5000\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 1272.7013\n",
      "Epoch 43/5000\n",
      "1/1 [==============================] - 0s 15ms/step - loss: 1271.5247\n",
      "Epoch 44/5000\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 1270.3490\n",
      "Epoch 45/5000\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 1269.1741\n",
      "Epoch 46/5000\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 1268.0002\n",
      "Epoch 47/5000\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 1266.8274\n",
      "Epoch 48/5000\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 1265.6550\n",
      "Epoch 49/5000\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 1264.4838\n",
      "Epoch 50/5000\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 1263.3134\n",
      "Epoch 51/5000\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 1262.1440\n",
      "Epoch 52/5000\n",
      "1/1 [==============================] - 0s 14ms/step - loss: 1260.9752\n",
      "Epoch 53/5000\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 1259.8073\n",
      "Epoch 54/5000\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 1258.6406\n",
      "Epoch 55/5000\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 1257.4746\n",
      "Epoch 56/5000\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 1256.3094\n",
      "Epoch 57/5000\n",
      "1/1 [==============================] - 0s 17ms/step - loss: 1255.1451\n",
      "Epoch 58/5000\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 1253.9818\n",
      "Epoch 59/5000\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 1252.8192\n",
      "Epoch 60/5000\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 1251.6576\n",
      "Epoch 61/5000\n",
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     ]
    },
    {
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     "output_type": "stream",
     "text": [
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    },
    {
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     "output_type": "stream",
     "text": [
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
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    {
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     "output_type": "stream",
     "text": [
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     ]
    },
    {
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     "output_type": "stream",
     "text": [
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    },
    {
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     "output_type": "stream",
     "text": [
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     "text": [
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "Epoch 4518/5000\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 109.5179\n",
      "Epoch 4519/5000\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 109.5163\n",
      "Epoch 4520/5000\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 109.5146\n",
      "Epoch 4521/5000\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 109.5130\n",
      "Epoch 4522/5000\n",
      "1/1 [==============================] - 0s 14ms/step - loss: 109.5114\n",
      "Epoch 4523/5000\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 109.5098\n",
      "Epoch 4524/5000\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 109.5081\n",
      "Epoch 4525/5000\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 109.5065\n",
      "Epoch 4526/5000\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 109.5049\n",
      "Epoch 4527/5000\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 109.5032\n",
      "Epoch 4528/5000\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 109.5016\n",
      "Epoch 4529/5000\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 109.5000\n",
      "Epoch 4530/5000\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 109.4983\n",
      "Epoch 4531/5000\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 109.4967\n",
      "Epoch 4532/5000\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 109.4950\n",
      "Epoch 4533/5000\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 109.4934\n",
      "Epoch 4534/5000\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 109.4918\n",
      "Epoch 4535/5000\n",
      "1/1 [==============================] - 0s 14ms/step - loss: 109.4901\n",
      "Epoch 4536/5000\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 109.4885\n",
      "Epoch 4537/5000\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 109.4868\n",
      "Epoch 4538/5000\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 109.4852\n",
      "Epoch 4539/5000\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 109.4836\n",
      "Epoch 4540/5000\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 109.4819\n",
      "Epoch 4541/5000\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 109.4803\n",
      "Epoch 4542/5000\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 109.4786\n",
      "Epoch 4543/5000\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 109.4770\n",
      "Epoch 4544/5000\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 109.4753\n",
      "Epoch 4545/5000\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 109.4737\n",
      "Epoch 4546/5000\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 109.4721\n",
      "Epoch 4547/5000\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 109.4704\n",
      "Epoch 4548/5000\n",
      "1/1 [==============================] - 0s 14ms/step - loss: 109.4688\n",
      "Epoch 4549/5000\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 109.4671\n",
      "Epoch 4550/5000\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 109.4655\n",
      "Epoch 4551/5000\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 109.4638\n",
      "Epoch 4552/5000\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 109.4622\n",
      "Epoch 4553/5000\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 109.4605\n",
      "Epoch 4554/5000\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 109.4589\n",
      "Epoch 4555/5000\n",
      "1/1 [==============================] - 0s 14ms/step - loss: 109.4573\n",
      "Epoch 4556/5000\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 109.4556\n",
      "Epoch 4557/5000\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 109.4539\n",
      "Epoch 4558/5000\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 109.4523\n",
      "Epoch 4559/5000\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 109.4506\n",
      "Epoch 4560/5000\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 109.4490\n",
      "Epoch 4561/5000\n",
      "1/1 [==============================] - 0s 14ms/step - loss: 109.4473\n",
      "Epoch 4562/5000\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 109.4456\n",
      "Epoch 4563/5000\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 109.4440\n",
      "Epoch 4564/5000\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 109.4423\n",
      "Epoch 4565/5000\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 109.4407\n",
      "Epoch 4566/5000\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 109.4390\n",
      "Epoch 4567/5000\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 109.4374\n",
      "Epoch 4568/5000\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 109.4357\n",
      "Epoch 4569/5000\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 109.4341\n",
      "Epoch 4570/5000\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 109.4324\n",
      "Epoch 4571/5000\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 109.4308\n",
      "Epoch 4572/5000\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 109.4291\n",
      "Epoch 4573/5000\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 109.4274\n",
      "Epoch 4574/5000\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "IOPub message rate exceeded.\n",
      "The notebook server will temporarily stop sending output\n",
      "to the client in order to avoid crashing it.\n",
      "To change this limit, set the config variable\n",
      "`--NotebookApp.iopub_msg_rate_limit`.\n",
      "\n",
      "Current values:\n",
      "NotebookApp.iopub_msg_rate_limit=1000.0 (msgs/sec)\n",
      "NotebookApp.rate_limit_window=3.0 (secs)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "model.fit(data.Education,data.Income,epochs=5000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "9a507cfe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[64.649666]], dtype=float32)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.predict([20])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "283cc9ba",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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   "mimetype": "text/x-python",
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   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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